Update README.md

README.md

@@ -6,25 +6,26 @@ pipeline_tag: image-to-text
 tags:
 - HTR
 ---
+
 # Model Card: Swedish National Archives HTR Pipeline
 
 ## Model Description
-The Swedish National Archives presents an end-to-end Handwritten Text Recognition (HTR) pipeline for running-text documents ranging from 1600 to 1900. The pipeline consists of the following components:
+The Swedish National Archives presents an end-to-end Handwritten Text Recognition (HTR) pipeline for running-text documents ranging from the 16th to the 19th century. The pipeline consists of the following components:
 
 1. **RTMDet Instance Segmentation Models**: The pipeline utilizes two RTMDet instance segmentation models, trained using MMDetection. The first model is designed to segment text regions within the documents, while the second model focuses on segmenting text lines within these regions. These models enable the identification and localization of text areas, which is a crucial step in the HTR pipeline.
 
 2. **SATRN HTR Model**: The pipeline incorporates a SATRN (Spatial Attention Transformer Networks) model, trained using MMOCR (OpenMMLab's OCR toolbox). SATRN is a state-of-the-art model for HTR tasks and provides accurate recognition of handwritten text. The SATRN model is trained specifically to handle the characteristics and challenges of handwritten text present in the Swedish National Archives' documents.
 
-The models are designed to provide a generic pipeline for handwritten text recognition, offering robust performance for documents from the years 1600 to 1900.
+The models are designed to provide a generic pipeline for handwritten text recognition, offering robust performance for documents from the 16th to the 19th century.
 
 ## Intended Use
 The Swedish National Archives HTR pipeline is intended to be used for the following purposes:
 
-- Handwritten Text Recognition: The pipeline enables the automatic recognition of handwritten text in running-text documents from the 17th to the 19th century. It can be utilized by researchers, historians, and archivists to efficiently transcribe and analyze historical texts.
+- Handwritten Text Recognition: The pipeline enables the automatic recognition of handwritten text in running-text documents from the 16th to the 19th century. It can be utilized by researchers, historians, and archivists to efficiently transcribe and analyze historical texts.
 
 - Document Digitization: The pipeline aids in the process of digitizing archival documents by automating the extraction and transcription of handwritten text. This facilitates broader accessibility and preservation of historical materials.
 
-It's important to note that the pipeline is optimized for running-text documents from the specified time period and may not perform optimally for other types of documents or handwriting styles.
+It's important to note that the pipeline is optimized for running-text documents from the specified time period and may not perform optimally for other types of documents or handwriting styles. Additionally, it is currently more suitable for documents from books rather than complex layouts or tabular data found in newspapers.
 
 ## Performance and Limitations
 The performance of the Swedish National Archives HTR pipeline is influenced by several factors:
@@ -33,14 +34,14 @@ The performance of the Swedish National Archives HTR pipeline is influenced by s
 
 - **Speed**: The pipeline aims to provide real-time or near real-time performance for efficient processing of handwritten text documents. The speed may vary depending on the hardware used for inference.
 
-- **Document Specificity**: The pipeline is specifically trained for running-text documents from the 17th to the 19th century. It may not perform optimally for documents outside this time range or for documents with unique characteristics or handwriting styles not covered by the training data.
+- **Document Specificity**: The pipeline is specifically trained for running-text documents from the 16th to the 19th century. It may not perform optimally for documents outside this time range or for documents with unique characteristics or handwriting styles not covered by the training data.
 
 - **Language Limitations**: The pipeline is tailored for Swedish text recognition. While it may handle other languages to some extent, its performance may not be as accurate as for Swedish.
 
 - **Handwriting Style**: The pipeline is optimized for the cursive handwriting style prevalent in the historical documents of the Swedish National Archives. It may not perform as well for other handwriting styles, such as block letters or highly stylized scripts.
 
 ## Training Data
-The Swedish National Archives HTR pipeline was trained using a diverse dataset of running-text documents from the 17th to the 19th century. The training data includes various types of historical texts, such as letters, manuscripts, and official records.
+The Swedish National Archives HTR pipeline was trained using a diverse dataset of running-text documents from the 16th to the 19th century. The training data includes various types of historical texts, such as letters, manuscripts, and official records.
 
 The dataset comprises both high-quality and challenging examples to ensure the models' robustness. It covers a wide range of handwriting styles, legibility levels, and document conditions.
 
@@ -65,10 +66,13 @@ Although the Swedish National Archives HTR pipeline has been trained and optimiz
 - **User Feedback**: Users are encouraged to provide feedback on the pipeline's performance, identify issues, and report any potential biases or limitations. This feedback can contribute to refining the pipeline and addressing concerns.
 
 ## Conclusion
-The Swedish National Archives HTR pipeline offers a powerful solution for automatic handwritten text recognition in running-text documents from the 17th to the 19th century. It leverages instance segmentation models for text region and line extraction, combined with a state-of-the-art SATRN model for accurate recognition. While the pipeline demonstrates high accuracy, speed, and flexibility, users should be aware of its limitations and consider the ethical implications of using historical data. Regular updates and user feedback are crucial for maintaining and improving the pipeline's performance.
+The Swedish National Archives HTR pipeline offers a powerful solution for automatic handwritten text recognition in running-text documents from the 16th to the 19th century. It leverages instance segmentation models for text region and line extraction, combined with a state-of-the-art SATRN model for accurate recognition. While the pipeline demonstrates high accuracy, speed, and flexibility, users should be aware of its limitations and consider the ethical implications of using historical data. Regular updates and user feedback are crucial for maintaining and improving the pipeline's performance.
 
 For further inquiries or assistance, please reach out to the Swedish National Archives.
 
+## Demo
+You can try out a demo of the Swedish National Archives HTR pipeline at [Riksarkivet HTR Demo](https://huggingface.co/spaces/Riksarkivet/htr_demo).
+
 ## References
 If you would like to learn more about the Swedish National Archives HTR pipeline or access the training data, please refer to the following resources:
 
@@ -76,4 +80,4 @@ If you would like to learn more about the Swedish National Archives HTR pipeline
 - [MMDetection](https://github.com/open-mmlab/mmdetection)
 - [MMOCR](https://github.com/open-mmlab/mmocr)
 - [SATRN Paper](https://arxiv.org/abs/2012.05483)
-- [OpenMMLab OCR Toolbox](https://openmmlab.com/mmocr/)
+- [OpenMMLab OCR Toolbox](https://openmmlab.com/mmocr/)